Abstract
Mental health problems are common in college students even in the late stage of the coronavirus disease 2019 (COVID-19) outbreak. Network analysis is a novel approach to explore interactions of mental disorders at the symptom level. The aim of this study was to elucidate characteristics of depressive and anxiety symptoms network in college students in the late stage of the COVID-19 outbreak. A total of 3062 college students were included. The seven-item Generalized Anxiety Disorder Scale (GAD-7) and nine-item Patient Health Questionnaire (PHQ-9) were used to measure anxiety and depressive symptoms, respectively. Central symptoms and bridge symptoms were identified based on centrality and bridge centrality indices, respectively. Network stability was examined using the case-dropping procedure. The strongest direct relation was between anxiety symptoms "Nervousness" and "Uncontrollable worry". "Fatigue" has the highest node strength in the anxiety and depression network, followed by "Excessive worry", "Trouble relaxing", and "Uncontrollable worry". "Motor" showed the highest bridge strength, followed by "Feeling afraid" and "Restlessness". The whole network was robust in both stability and accuracy tests. Central symptoms "Fatigue", "Excessive worry", "Trouble relaxing" and "Uncontrollable worry", and critical bridge symptoms "Motor", "Feeling afraid" and "Restlessness" were highlighted in this study. Targeting interventions to these symptoms may be important to effectively alleviate the overall level of anxiety and depressive symptoms in college students.